Mapping the distribution of conformational information throughout a protein sequence.

Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Roque Sáenz Peña 180, (1876) Bernal, Buenos Aires, Argentina.
Journal of Molecular Biology (Impact Factor: 3.91). 05/2006; 358(1):280-8. DOI: 10.1016/j.jmb.2006.01.095
Source: PubMed

ABSTRACT The three-dimensional structure of protein is encoded in the sequence, but many amino acid residues carry no essential conformational information, and the identity of those that are structure-determining is elusive. By circular permutation and terminal deletion, we produced and purified 25 Bacillus licheniformis beta-lactamase (ESBL) variants that lack 5-21 contiguous residues each, and collectively have 82% of the sequence and 92% of the non-local atom-atom contacts eliminated. Circular dichroism and size-exclusion chromatography showed that most of the variants form conformationally heterogeneous mixtures, but by measuring catalytic constants, we found that all populate, to a greater or lesser extent, conformations with the essential features of the native fold. This suggests that no segment of the ESBL sequence is essential to the structure as a whole, which is congruent with the notion that local information and modular organization can impart most of the tertiary fold specificity and cooperativity.

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    ABSTRACT: Circular permutation (CP) is a protein structural rearrangement phenomenon, through which nature allows structural homologs to have different locations of termini and thus varied activities, stabilities and functional properties. It can be applied in many fields of protein research and bioengineering. The limitation of applying CP lies in its technical complexity, high cost and uncertainty of the viability of the resulting protein variants. Not every position in a protein can be used to create a viable circular permutant, but there is still a lack of practical computational tools for evaluating the positional feasibility of CP before costly experiments are carried out. We have previously designed a comprehensive method for predicting viable CP cleavage sites in proteins. In this work, we implement that method into an efficient and user-friendly web server named CPred (CP site predictor), which is supposed to be helpful to promote fundamental researches and biotechnological applications of CP. The CPred is accessible at
    Nucleic Acids Research 06/2012; 40(Web Server issue):W232-7. · 8.81 Impact Factor
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    ABSTRACT: β-lactamases confer antibiotic resistance, one of the most serious world-wide health problems, and are an excellent theoretical and experimental model in the study of protein structure, dynamics and evolution. Bacillus licheniformis exo-small penicillinase (ESP) is a Class-A β-lactamase with three tryptophan residues located in the protein core. Here, we report the 1.7-Å resolution X-ray structure, catalytic parameters, and thermodynamic stability of ESP(ΔW), an engineered mutant of ESP in which phenylalanine replaces the wild-type tryptophan residues. The structure revealed no qualitative conformational changes compared with thirteen previously reported structures of B. licheniformis β-lactamases (RMSD = 0.4-1.2 Å). However, a closer scrutiny showed that the mutations result in an overall more compact structure, with most atoms shifted toward the geometric center of the molecule. Thus, ESP(ΔW) has a significantly smaller radius of gyration (R(g)) than the other B. licheniformis β-lactamases characterized so far. Indeed, ESP(ΔW) has the smallest R(g) among 126 Class-A β-lactamases in the Protein Data Bank (PDB). Other measures of compactness, like the number of atoms in fixed volumes and the number and average of noncovalent distances, confirmed the effect. ESP(ΔW) proves that the compactness of the native state can be enhanced by protein engineering and establishes a new lower limit to the compactness of the Class-A β-lactamase fold. As the condensation achieved by the native state is a paramount notion in protein folding, this result may contribute to a better understanding of how the sequence determines the conformational variability and thermodynamic stability of a given fold.
    Protein Science 04/2012; 21(7):964-76. · 2.74 Impact Factor
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    ABSTRACT: Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology.
    PLoS ONE 01/2012; 7(2):e31791. · 3.53 Impact Factor

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